Suffix arrays: a new method for on-line string searches
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Universal Data Compression Based on the Burrows-Wheeler Transformation: Theory and Practice
IEEE Transactions on Computers
An analysis of the Burrows—Wheeler transform
Journal of the ACM (JACM)
Second step algorithms in the Burrows-Wheeler compression algorithm
Software—Practice & Experience
A Fast Block-Sorting Algorithm for Lossless Data Compression
DCC '97 Proceedings of the Conference on Data Compression
A Corpus for the Evaluation of Lossless Compression Algorithms
DCC '97 Proceedings of the Conference on Data Compression
Modifications of the Burrows and Wheeler Data Compression Algorithm
DCC '99 Proceedings of the Conference on Data Compression
DNA Sequence Compression Using the Burrows-Wheeler Transform
CSB '02 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Rapid identification of repeated patterns in strings, trees and arrays
STOC '72 Proceedings of the fourth annual ACM symposium on Theory of computing
A Fast Algorithms for Making Suffix Arrays and for Burrows-Wheeler Transformation
DCC '98 Proceedings of the Conference on Data Compression
The Context Trees of Block Sorting Compression
DCC '98 Proceedings of the Conference on Data Compression
Generalization of the BWT Transformation and Inversion Ranks
DCC '02 Proceedings of the Data Compression Conference
Image Compression Using Blocksort
DCC '01 Proceedings of the Data Compression Conference
Prototyping of Efficient Hardware Algorithms for Data Compression in Future Communication Systems
RSP '01 Proceedings of the 12th International Workshop on Rapid System Prototyping
Antisequential Suffix Sorting for BWT-Based Data Compression
IEEE Transactions on Computers
The Performance of Linear Time Suffix Sorting Algorithms
DCC '05 Proceedings of the Data Compression Conference
Unifying The Burrows-Wheeler and The Schindler Transforms
DCC '06 Proceedings of the Data Compression Conference
An Efficient Algorithm For The Inverse ST Problem
DCC '07 Proceedings of the 2007 Data Compression Conference
Linear-time construction of suffix arrays
CPM'03 Proceedings of the 14th annual conference on Combinatorial pattern matching
Space efficient linear time construction of suffix arrays
CPM'03 Proceedings of the 14th annual conference on Combinatorial pattern matching
Simple linear work suffix array construction
ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
Computing Inverse ST in Linear Complexity
CPM '08 Proceedings of the 19th annual symposium on Combinatorial Pattern Matching
Extension and faster implementation of the GRP transform for lossless compression
CPM'10 Proceedings of the 21st annual conference on Combinatorial pattern matching
Computing the inverse sort transform in linear time
ACM Transactions on Algorithms (TALG)
Revisiting bounded context block-sorting transformations
Software—Practice & Experience
Hi-index | 14.98 |
As an important variant of the Burrows-WheelerTransform (BWT), the Sort Transform (ST) can speed up thetransformation by sorting only a portion of the matrix. However,because the currently known inverse ST algorithms need toretrieve the complete k-order contexts and use hash tables, theyare less efficient than the inverse BWT. In this paper, we proposethree fast and memory-efficient inverse ST algorithms. The firstalgorithm uses two auxiliary vectors to replace the hash tables.The algorithm achieves O(kN) time and space complexities for atext of N characters under the context order k. The second usestwo additional compact "alternate vectors" to further eliminatethe need to restore all the k-order contexts and achieve O(N)space complexity. And the third uses a "doubling technique" tofurther reduce the time complexity to O(N log2 k). The hallmarkof these three algorithms is that they can invert ST in a mannersimilar to inverting BWT in that they all make use of precalculatedauxiliary mapping vectors and require no hash tables.These unifying algorithms can also better explain the connectionbetween the BWT and the ST: their forward components can notonly be performed by the same algorithm framework, but theirrespective inverse components can also be efficiently conductedby the unifying algorithm framework proposed in the presentwork.